Visual tracking has been studied for several decades but continues to draw significant attention because of its critical role in many applications. Recent years have seen greater interest in the use of correlation filters in visual tracking systems, owing to their extremely compelling results in different competitions and benchmarks. However, there is still a need to improve the overall tracking capability to counter various tracking issues, including large scale variation, occlusion, and deformation. This paper presents an appealing tracker with robust scale estimation, which can handle the problem of fixed template size in Kernelized Correlation Filter (KCF) tracker with no significant decrease in the speed. We apply the discriminative correlation filter for scale estimation as an independent part after finding the optimal translation based on the KCF tracker. Compared to an exhaustive scale space search scheme, our approach provides improved performance while being computationally efficient. In order to reveal the effectiveness of our approach, we use benchmark sequences annotated with 11 attributes to evaluate how well the tracker handles different attributes. Numerous experiments demonstrate that the proposed algorithm performs favorably against several state-of-the-art algorithms. Appealing results both in accuracy and robustness are also achieved on all 51 benchmark sequences, which proves the efficiency of our tracker.

A compact millimeter-wave three-pole dual-band bandpass filter (BPF) by using substrate-integrated waveguide (SIW) dual-mode cavities is developed in this paper. The proposed filter consists of three SIW dual-mode cavities, in which the TE201 and TE102 modes are used to form two passbands. The center frequencies of the two passbands can be readily changed by varying the lengths and/or widths of the SIW cavities. Meanwhile three transmission zeros are produced with appropriate design of the input and output of the SIW cavities, which increase significantly the isolation between the two passbands and their roll-off rate of attenuations. The dual-band BPF filter is designed, fabricated and measured. The measured center frequencies of the two passbands are 26.75GHz and 31.55GHz, respectively. The 3dB-passbands are 26.35-27.15GHz (3%) and 31.29-31.81GHz (1.6%), respectively, with maximum insertion loss of 2.64dB and 4.2dB, respectively, and return loss larger than 12dB in both passbands. A good agreement between the simulated and measured filter characteristics is obtained.

User-based and item-based collaborative filtering (CF) are two of the most important and popular techniques in recommender systems. Although they are widely used, there are still some limitations, such as not being well adapted to the sparsity of data sets, failure to consider the hierarchical structure of the items, and changes in users' interests when calculating the similarity of items. To overcome these shortcomings, we propose an evolutionary approach based on hierarchical structure for dynamic recommendation system named Hierarchical Temporal Collaborative Filtering (HTCF). The main contribution of the paper is displayed in the following two aspects. One is the exploration of hierarchical structure between items to improve similarity, and the other is the improvement of the prediction accuracy by utilizing a time weight function. A unique feature of our method is that it selects neighbors mainly based on hierarchical structure between items, which is more reliable than co-rated items utilized in traditional CF. To the best of our knowledge, there is little previous work on researching CF algorithm by combining object implicit or latent object-structure relations. The experimental results show that our method outperforms several current recommendation algorithms on recommendation accuracy (in terms of MAE).

A novel scheme to implement a filter bank multicarrier/offset quadrature amplitude modulation (FBMC/OQAM) transmission system is proposed. This is achieved by replacing the existing polyphase filter banks based on FFT/IFFT with fast filter bank (FFB) in order to utilize its good properties such as cascaded structure and high frequency selectivity with a comparable complexity as FFT/IFFT. Although this topic is not addressed in the literature, the impulse response of the prototype filter for each stage within FFB can still be obtained by using an optimization technique, which is used to minimize the distortion caused by intersymbol and interchannel interferences (ISI and ICI) of the proposed FBMC/OQAM transmission system, subject to allowable ripples in the passband and stopband. As a result, the relationship between two-path prototype filters in each subfilter should be modified with a general form accordingly. Simulations show that the number of multiplications required by the proposed scheme is smaller than that needed by the polyphase filter banks solution based on FFT/IFFT. Furthermore, the suitability of the design of prototype filters and the validation can be also supported by the results.

In this paper a new method for noise removal from single-trial event-related potentials recorded with a multi-channel electroencephalogram is addressed. An observed signal is separated into multiple signals with a multi-channel Wiener filter whose coefficients are estimated based on parameter estimation of a probabilistic generative model that locally models the amplitude of each separated signal in the time-frequency domain. Effectiveness of using prior information about covariance matrices to estimate model parameters and frequency dependent covariance matrices were shown through an experiment with a simulated event-related potential data set.

A non-photorealistic rendering method creates oil-film-like images, expressed with colorful, smooth curves similar to the oil films generated on the surface of glass or water, from color photo images. The proposed method generates oil-film-like images through iterative processing between a bilateral infra-envelope filter and an unsharp mask. In order to verify the effectiveness of the proposed method, tests using a Lena image were performed, and visual assessment of oil-film-like images was conducted for changes in appearance as the parameter values of the proposed method were varied. As a result of tests, the optimal value of parameters was found for generating oil-film patterns.

This paper proposes a high clutter-rejection technique for wall-penetrating frequency-modulated continuous-wave (FMCW) radar. FMCW radars are widely used, as they moderate the receiver saturation problem in wall-penetrating applications by attenuating short-range clutter such as wall-clutter. However, conventional FMCW radars require a very high-order high-pass filter (HPF) to attenuate short-range clutter. A delay-line (DL) is exploited to overcome this problem. Time-delay shifts beat frequencies formed by reflection waves. This means that a proper time-delay increases the ratio of target-beat frequency to clutter-beat frequency. Consequently, low-order HPF fully attenuates short-range clutter. A third-order HPF rejects more than 20 dB and 30 dB for clutter located at 6 m and 3 m, respectively, with a target located at 9 m detection with a 10,000 GHz/s chirp rate and a 28 ns delay-line.

Maneuvering target tracking under mixed line-of-sight/non-line-of-sight (LOS/NLOS) conditions has received considerable interest in the last decades. In this paper, a hierarchical interacting multiple model (HIMM) method is proposed for estimating target position under mixed LOS/NLOS conditions. The proposed HIMM is composed of two layers with Markov switching model. The purpose of the upper layer, which is composed of two interacting multiple model (IMM) filters in parallel, is to handle the switching between the LOS and the NLOS environments. To estimate the target kinetic variables (position, speed and acceleration), the unscented Kalman filter (UKF) with the current statistical (CS) model is used in the lower-layer. Simulation results demonstrate the effectiveness and superiority of the proposed method, which obtains better tracking accuracy than the traditional IMM.

This paper proposes a new class of Hilbert pairs of almost symmetric orthogonal wavelet bases. For two wavelet bases to form a Hilbert pair, the corresponding scaling lowpass filters are required to satisfy the half-sample delay condition. In this paper, we design simultaneously two scaling lowpass filters with the arbitrarily specified flat group delay responses at ω=0, which satisfy the half-sample delay condition. In addition to specifying the number of vanishing moments, we apply the Remez exchange algorithm to minimize the difference of frequency responses between two scaling lowpass filters, in order to improve the analyticity of complex wavelets. The equiripple behavior of the error function can be obtained through a few iterations. Therefore, the resulting complex wavelets are orthogonal and almost symmetric, and have the improved analyticity. Finally, some examples are presented to demonstrate the effectiveness of the proposed design method.

The individual steps of UV imprint lithography have been explained in detail from the points of manufacturing nano-structures. The applications to photonic devices have been also introduced.

We design a new hash table for high-speed networking that reduces main memory accesses even when the ratio of inserted items to the table size is high, at which point previous schemes no longer work. This improvement comes from a new design of a summary, called expanded keys, exploiting recent multiple hash functions and Bloom filter theories.

Ultra-wideband (UWB) communications is used for medical information communication technology (MICT) as a dependable and safe communication technology in recent years. On the other hand, there are existing various UWB systems that are not used for MICT. Generally, these UWB systems use almost the same frequency band. Therefore, they interfere to each other in general transmission channel environment. In our previous work, a novel UWB pulse shape modulation using modified Hermite pulse is proposed as a multiple user access scheme. In this paper, we propose a mitigation method for inter-user interference and inter-system interference using combination of orthogonal pulse shape modulation and orthogonal matched filter (OMF) detector. The purposes of our system are to detect all signals of users in the same UWB system and to reduce the unknown interference from other UWB systems at the same time. This paper provides performance evaluation results based on both of analytical and numerical evaluation. Simulation results show that the proposed system can detect the signals that were transmitted from the same UWB system using orthogonal pulse set, while the proposed system can reduce the interference from unknown UWB systems at the same time. The theoretical analysis is expected that noise tolerance of our proposal will be deteriorated in the additive Gaussian noise channel in comparison with the conventional matched filter. It is confirmed that the numerical evaluation illustrates such noise tolerance equivalent to the theoretical analysis result.

Cost aggregation is one of the most important steps in local stereo matching, while it is difficult to fulfill both accuracy and speed. In this letter, a novel cost aggregation, consisting of guidance image, fast aggregation function and simplified scan-line optimization, is developed. Experiments demonstrate that the proposed algorithm has competitive performance compared with the state-of-art aggregation methods on 32 Middlebury stereo datasets in both accuracy and speed.

A new design method for a high-order series-coupled microring filter using Chebyshev filter condition was proposed and its application to the design of a wavelength-selective switch (WSS) was discussed. In the proposed method, the propagation loss in a microring resonator, coupling loss at a coupler, and a free spectral ranges (FSR) in a microring resonator are considered for the first time. It was found that for high-order series coupled microring resonators, the WSS designed using Chebyshev condition has more boxlike filter responses and high extinction ratio, compared with that designed using Butterworth condition, in the case where the round-trip loss in a microring is relatively large. In addition, the fourth-order series-coupled microring WSS with boxlike responses was successfully designed, considering Vernier effect for a larger FSR and shift in resonant wavelength.

In this paper, an iterative optimal method is proposed to design the prototype filters for a fast filter bank (FFB) with low complexity, aiming to control the optimum ripple magnitude tolerance of each filter according to the overall specifications. This problem is formulated as an optimization problem for which the total number of multiplications is to be minimized subject to the constrained ripple in the passband and stopband. In the following, an iterative solution is proposed to solve this optimization problem for the purpose of obtaining the impulse response coefficients with low complexity at each stage. Simulations are conducted to verify the performance of the proposed scheme and show that compared with the original method, the proposed scheme can reduce about 24.24% of multiplications. In addition, the proposed scheme and the original method provide similar mean square error (MSE) and the mean absolute error (MAE) of the frequency response.

Noise and area consumption has been a trade-off in circuit design. Especially for switched-capacitor filters (SCF), kT/C noise gives a limitation to the minimum value of unit capacitance. In case of SCFs with a large capacitance spread, this limitation will result in a large area consumption due to large capacitors. This paper introduces a technique to reduce capacitance spread using charge scaling. It will be shown that this technique can reduce total capacitance of SCFs without deteriorating their noise performances. A design method to reduce the output noise of SC low-pass filters (LPF) based on the combination of cut-set scaling, charge scaling and adaptive configuration is proposed. The proposed technique can reduce the output noise voltage by 30% for small input signals.

Nowadays, with the development of online social networks (OSN), a mass of online social information has been generated in OSN, which has triggered research on social recommendation. Collaborative filtering, as one of the most popular techniques in social recommendation, faces several challenges, such as data sparsity, cold-start users and prediction quality. The motivation of our work is to deal with the above challenges by effectively combining collaborative filtering technology with social information. The trust relationship has been identified as a useful means of using social information to improve the quality of recommendation. In this paper, we propose a trust-based recommendation approach which uses GlobalTrust (GT) to represent the trust value among users as neighboring nodes. A matrix factorization based on singular value decomposition is used to get a trust network built on the GT value. The recommendation results are obtained through a modified random walk algorithm called GlobalTrustWalker. Through experiments on a real-world sparser dataset, we demonstrate that the proposed approach can better utilize users' social trust information and improve the recommendation accuracy on cold-start users.

This paper proposes a method based on modulation transfer function (MTF) to restore the power envelope of noisy reverberant speech by using a Kalman filter with linear prediction (LP). Its advantage is that it can simultaneously suppress the effects of noise and reverberation by restoring the smeared MTF without measuring room impulse responses. This scheme has two processes: power envelope subtraction and power envelope inverse filtering. In the subtraction process, the statistical properties of observation noise and driving noise for power envelope are investigated for the criteria of the Kalman filter which requires noise to be white and Gaussian. Furthermore, LP coefficients drastically affect the Kalman filter performance, and a method is developed for deriving LP coefficients from noisy reverberant speech. In the dereverberation process, an inverse filtering method is applied to remove the effects of reverberation. Objective experiments were conducted under various noisy reverberant conditions to evaluate how well the proposed Kalman filtering method based on MTF improves the signal-to-error ratio (SER) and correlation between restored power envelopes compared with conventional methods. Results showed that the proposed Kalman filtering method based on MTF can improve SER and correlation more than conventional methods.

This paper describes a fast and effective algorithm for refining the parameter estimates of multicomponent third-order polynomial phase signals (PPSs). The efficiency of the proposed algorithm is accompanied by lower signal-to-noise ratio (SNR) threshold, and computational complexity. A two-step procedure is used to estimate the parameters of multicomponent third-order PPSs. In the first step, an initial estimate for the phase parameters can be obtained by using fast Fourier transformation (FFT), k-means algorithm and three time positions. In the second step, these initial estimates are refined by a simple moving average filter and singular value decomposition (SVD). The SNR threshold of the proposed algorithm is lower than those of the non-linear least square (NLS) method and the estimation refinement method even though it uses a simple moving average filter. In addition, the proposed method is characterized by significantly lower complexity than computationally intensive NLS methods. Simulations confirm the effectiveness of the proposed method.

In this letter, an effective acoustic feedback cancellation algorithm is proposed based on the normalized sub-band adaptive filter (NSAF). To improve the confliction between fast convergence rate and low misalignment in the NSAF algorithm, a variable step size is designed to automatically vary according to the update state of the filter. The update state of the filter is adaptively detected via the normalized distance between the long term average and the short term average of the tap-weight vector. Simulation results demonstrate that the proposed algorithm has superior performance in terms of convergence rate and misalignment.